autograd 1.6.3-foss-2022b

Autograd can automatically differentiate native Python and Numpy code. It can handle a large subset of Python's features, including loops, ifs, recursion and closures, and it can even take derivatives of derivatives of derivatives. It supports reverse-mode differentiation (a.k.a. backpropagation), which means it can efficiently take gradients of scalar-valued functions with respect to array-valued arguments, as well as forward-mode differentiation, and the two can be composed arbitrarily. The main intended application of Autograd is gradient-based optimization.

Accessing autograd 1.6.3-foss-2022b

To load the module for autograd 1.6.3-foss-2022b please use this command on the BEAR systems (BlueBEAR, BEAR Cloud VMs, and CaStLeS VMs):

module load bear-apps/2022b
module load autograd/1.6.3-foss-2022b

BEAR Apps Version

2022b

Architectures

EL8-cascadelakeEL8-icelake

The listed architectures consist of two part: OS-CPU. The OS used is represented by EL and there are several different processor (CPU) types available on BlueBEAR. More information about the processor types on BlueBEAR is available on the BlueBEAR Job Submission page.

Extensions

  • autograd 1.6.3

More Information

For more information visit the autograd website.

Dependencies

This version of autograd has a direct dependency on: foss/2022b Python/3.10.8-GCCcore-12.2.0 SciPy-bundle/2023.02-gfbf-2022b

Required By

This version of autograd is a direct dependent of: Meep/1.28.0-foss-2022b

Other Versions

These versions of autograd are available on the BEAR systems (BlueBEAR, BEAR Cloud VMs, and CaStLeS VMs). These will be retained in accordance with our Applications Support and Retention Policy.

Last modified on 23rd November 2023